Gas chromatography-mass spectrometry determination of polycyclic aromatic hydrocarbons in water coupled with electro flotation-assisted emulsification liquid–liquid micro extraction

Polycyclic aromatic hydrocarbons are priority pollutants due to the very high toxicity. Therefore, to determine them, it is necessary to use sensitive methods with preconcentration. In the present study, a novel method named electroflotation-assisted deemulsification liquid–liquid microextraction combined with GC-MS analysis has been proposed for the preconcentration and determination of polycyclic aromatic hydrocarbons in water samples. The advantage of electroflotation deemulsification is the ease of changing the gas flow and size of gas micro-bubbles. The formation of gas micro-bubbles occurs on platinum electrodes soldered into a glass concentrator. Hexane, toluene and o-xylene were used as extractants. Application of extract capillary collection have solved the problem of the light extractant sampling. Dispersion of the extractant was performed by ultrasound. The volume of microextract was 7-10 µl. The recovery of polycyclic aromatic hydrocarbons from water was 62-95%. A DB-5 (5% phenyl + 95% polydimethylsiloxane) fused-silica capillary column (30 m ×0.25 mm i.d. and 0.25-µm film thickness)was applied for separation of the analytes. The limits of detection and quantification of polycyclic aromatic hydrocarbons achieved were at the level of 10-5–10-6 mgL-1 and  highly competitive with the best world results. The methods of accounting or elimination of systematic errors are proposed. Purification of solvents by Rayleigh distillation method allows to obtain samples with impurity content lower than (1-4)∙10-3 mgL-1. Containers for sampling and storage of samples to be analyzed should be made of borosilicate glass or quartz. The expanded uncertainty was calculated. It included precision, uncertainty of standards preparation, calibration, sample introduction, enrichment factor. The relative expanded uncertainty was at the level of 13-30%.

Author(s): Valentin A. Krylov

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